Assessing the performance of marine plastics cleanup technologies in Europe and North America. (1st May 2023) - Brouwer, Roy; Huang, Yichun; Huizenga, Tessa; Frantzi, Sofia; Le, Trang; Sandler, Jared; Dijkstra, Hanna; van Beukering, Pieter; Costa, Elisa; Garaventa, Francesca; Piazza, Veronica
Abstract: This study fills an important gap in policymaker understanding of the effectiveness and implementation costs of marine plastic cleanup technologies. Previous studies have mainly listed inventories of different plastic litter cleanup technologies, not systematically examined their cost-effectiveness. Through a survey in Europe and North America that asked for cost and cleanup capacity data, per kilogram cost figures were calculated for several categories of cleanup technologies, ranging from fixed-in-place filters in stormwater drainage systems to mobile skimmers on water. Mobile skimmers and dredgers appear to be most cost-effective. Adding performance criteria related to operational conditions and ease of use, such as energy use and economies of scale, dredgers and stormwater filters rank higher. Litter traps in drainage systems are most preferred when furthermore considering weather sensitivity and whether technologies operate standalone, making them an interesting complementary technology to skimmers and dredgers to prevent plastic litter from entering water courses. These results show how sensitive the outcome of the ranking is to the inclusion of additional operational criteria, how different categories of technologies can effectively be combined in the plastic waste supply chain, and what the cost implications are for the future upscaling of plastic litter cleanup technologies. Highlights: The cost-effectiveness of plastic cleanup technologies is not well understood. Technologies range from fixed-in-place filters in stormwater drainage to mobile water skimmers. In this study, water-based technologies appear to be most cost-effective. A combination of land-based and water-based technologies is preferred when adding performance criteria.